COMPUTATIONAL SOCIAL SCIENCE – Foundations of Agent Computing for Economics and Finance – Robert Axtell

When:
February 3, 2017 @ 3:00 pm – 4:30 pm
2017-02-03T15:00:00-05:00
2017-02-03T16:30:00-05:00
Where:
Center for Social Complexity Suite, 3rd Floor, Research Hall, Fairfax Campus
Cost:
Free
Contact:
Karen Underwood
7039939298

COMPUTATIONAL SOCIAL SCIENCE FRIDAY SEMINAR

Robert Axtell, Professor
Computational Social Science
Department of Computational and Data Sciences

Foundations of Agent Computing for Economics and Finance

Friday, February 3, 2017
Center for Social Complexity Suite
3rd Floor, Research Hall

In many ways economics and finance are fields for which the strengths of agent computing should lead researchers to become ‘early adopters,’ at least in comparison to less quantitative social sciences. While this has happened to some extent, it is also true that methodological norms are strong in economics and finance, meaning that innovations will always face resistance. In this talk I will preview the ideas from a paper, co-authored with J. Doyne Farmer of the University of Oxford’s Complexity Economics Programme, geared toward enticing economists toward agent-based modeling. I will contrast the process-based, procedural explanations of social phenomena that result from agent computing with the substantive but often static explanations that are more conventional in economic theory. The role of agents who learn will be highlighted. Next, the ability of agent computing to use all available hardware resources—the ‘small compile time, large run time’ character of ABMs–will be surveyed and compared with standard numerical economics. Then we ask whether having better, more user friendly software could substantially increase the rate of adoption of agents among economists. Finally, we suggest that technologies for systematic parallelization of agent models might go far as a ‘killer app’ insofar as it would permit the creation of large-scale models applicable to a wide variety of policy problems. For each of these arguments an illustrative example will be provided. I will conclude with a brief discussion of bottlenecks that appear to be limiting the progress of agent computing in economics and finance at the present time.